Title :
The Heuristic Static Load-Balancing Algorithm Applied to the Community Earth System Model
Author :
Alexeev, Yuri ; Mickelson, Sheri ; Leyffer, Sven ; Jacob, Robert ; Craig, Ashley
Author_Institution :
Leadership Comput. Facility, Argonne Nat. Lab., Argonne, IL, USA
Abstract :
We propose to use the heuristic static load-balancing (HSLB) algorithm for solving load-balancing problems in the Community Earth System Model (CESM), a climate model, using fitted benchmark data as an alternative to the current manual approach. The problem of allocating the optimal number of CPU cores to CESM components is formulated as a mixed-integer nonlinear optimization problem which is solved by using an optimization branch-and-bound solver implemented in the MINLP package MINOTAUR. The key feature of the branch-and-bound method is that it guarantees to provide an optimal solution or show that none exists. Our algorithm was tested for the 1° and 1/8° resolution simulations on 32,768 nodes (131,072 cores) of IBM Blue Gene/P where we consistently achieved well load-balanced results. This work is a part of a broader effort to eliminate the need for manual tuning of the code for each platform and simulation type, improve the performance and scalability of CESM, and develop automated tools to achieve these goals.
Keywords :
Earth; environmental factors; geophysics computing; integer programming; nonlinear programming; parallel processing; resource allocation; tree searching; CPU cores; IBM Blue Gene/P; MINLP package; MINOTAUR; automated tools; climate model; community Earth system model; fitted benchmark data; heuristic static load-balancing algorithm; load-balancing problem solving; mixed-integer nonlinear optimization problem; optimal solution; optimization branch-and-bound solver; Atmospheric modeling; Ice; Layout; Load modeling; Mathematical model; Optimization; Program processors; climate modeling; constrained optimization; global optimization; heuristic algorithm; integer programming; nonlinear programming; static load balancing;
Conference_Titel :
Parallel & Distributed Processing Symposium Workshops (IPDPSW), 2014 IEEE International
Conference_Location :
Phoenix, AZ
Print_ISBN :
978-1-4799-4117-9
DOI :
10.1109/IPDPSW.2014.177